📊 Sentiment Analysis Tool

A powerful web application that analyzes text sentiment in real-time, providing deep insights into emotional tone, polarity, and emotional characteristics. Built with modern web technologies for accurate and instant sentiment detection.

🖥️ Home Page Preview

🌐 Live Demo

Access the live application at: https://sentimentv1.netlify.app/

✨ Features

⚡ Real-time sentiment analysis

• Instant Sentiment Detection: Get immediate feedback as you type.
• Live Polarity Scoring: Dynamic positive/negative/neutral scoring.
• Continuous Emotion Tracking: Real-time emotion detection updates.

📊 Comprehensive Insights

• Detailed Polarity Breakdown: Percentage-based sentiment scoring.
• Emotion Classification: Identify specific emotions (joy, anger, sadness, etc.)
• Visual Analytics: Interactive charts and graphs for data visualization.

💾 Data Management

• Analysis History: Automatic logging of previous sentiment analyses.
• Session Persistence: Maintain your analysis history across sessions.
• Export Capabilities: Save or export results for further analysis.

📱 User Experience

• Responsive Design: Optimized for desktop, tablet, and mobile devices.
• Intuitive Interface: Clean, modern, and user-friendly design.
• Accessibility Focused: Built with accessibility best practices.

🛠️ Technology Stack

Frontend Development

• ⚡ JavaScript (ES6+) - Core programming language.
• 🎨 HTML5 & CSS3 - Modern web standards and styling.
• ⚛️ React - Component-based UI library.
• 💨 Tailwind CSS - Utility-first CSS framework.

APIs & Services

• 🧠 Gemini API - Advanced Natural Language Processing.
• ☁️ Netlify - Cloud hosting and deployment platform.

Data Visualization

• 📈 Chart.js - Interactive charts and data visualization.
• 📊 Custom Visualizations - Tailored sentiment display components.

🚀 Getting Started

Prerequisites

• ⚙️ Node.js (version 16.0 or higher).
• 📦 npm (version 8.0 or higher)/yarn.

Installation

• Clone the repository:

  git clone https://github.com/SiyamthandaD/Sentiment-Application.git
  cd Sentiment-Application

• Install dependencies:

   npm install
   # or
   yarn install

• Set up environment variables (if required)

  # Create a .env file in the root directory
  # Add your API keys and configuration
  REACT_APP_GEMINI_API_KEY=your_api_key_here

• Run the development server:

  npm start
  # or
  yarn start

• Open your browser Navigate to http://localhost:3000 to view the application

Available Scripts

• npm start - Runs the app in development mode.
• npm run build - Builds the app for production.
• npm test - Launches the test runner.
• npm run eject - Ejects from Create React App (one-way operation)

💡 Usage Guide

• Basic Text Analysis
  • Enter your text in the input field.
  • View real-time sentiment results.
  • Analyze polarity scores and emotional tone.
• Advanced Features
  • Explore detailed emotion breakdowns.
  • Review historical analysis data.
  • Export results for reporting.
• API Integration
  • Connect with Google Cloud Natural Language API.
  • Customize analysis parameters.
  • Scale for high-volume text processing.

📁 Project Structure

• Sentiment Application

  Sentiment-Application/
  ├── public/                     # Static assets
  │   ├── index.html              # Main HTML template
  │   ├── favicon.ico             # Application favicon
  │   └── manifest.json           # PWA manifest
  ├── src/                        # Source code
  │   ├── components/             # React components
  │   │   ├── AnalysisChart/      # Data visualization components
  │   │   ├── EmotionDisplay/     # Emotion visualization
  │   │   ├── HistoryPanel/       # Analysis history
  │   │   ├── InputArea/          # Text input components
  │   │   └── ResultsPanel/       # Results display
  │   ├── services/               # API and external services
  │   │   ├── geminiAPI.js        # Gemini API integration
  │   │   └── sentimentService.js # Sentiment analysis logic
  │   ├── utils/                  # Utility functions
  │   │   ├── textProcessor.js    # Text preprocessing
  │   │   └── formatters.js       # Data formatting
  │   ├── hooks/                  # Custom React hooks
  │   │   ├── useSentiment.js     # Sentiment analysis hook
  │   │   └── useHistory.js       # History management
  │   ├── styles/                 # Styling files
  │   │   ├── tailwind.css        # Tailwind imports
  │   │   └── components.css      # Component-specific styles
  │   ├── App.js                  # Root application component
  │   ├── App.css                 # Main application styles
  │   └── index.js                # Application entry point
  ├── package.json                # Project dependencies and scripts
  └── netlify.toml                # Netlify deployment configuration
  

Key Components

• InputArea - Text input and real-time processing.
• ResultsPanel - Display sentiment scores and analysis.
• AnalysisChart - Visual representation of sentiment data.
• EmotionDisplay - Detailed emotion classification.
• HistoryPanel - Previous analysis tracking.

🔌 API Integration

Gemini API Configuration

• The application integrates with Google's Gemini API for advanced natural language processing:

  // Example API integration
  const analyzeSentiment = async (text) => {
    const response = await fetch('https://api.gemini.google.com/v1/analyze', {
      method: 'POST',
      headers: {
        'Authorization': `Bearer ${apiKey}`,
        'Content-Type': 'application/json'
      },
      body: JSON.stringify({ text: text })
    });
    return await response.json();
  };
  

🚀 Deployment

Netlify Deployment

• The application is configured for seamless deployment on Netlify:
  • Automatic Deployments: Connected to GitHub for CI/CD.
  • Environment Variables: Secure API key management.
  • Performance Optimization: Built-in caching and CDN.

Build for Production

• This creates an optimized production build in the build folder.

  npm run build
  

🤝 Contributing

We welcome contributions from the community! Whether you're fixing bugs, adding new features, or improving documentation, your help is appreciated.

Contribution Workflow

• Fork the repository.
• Create a feature branch

  git checkout -b feature/amazing-feature

• Commit your changes

  git commit -m 'Add some amazing feature'

• Push to the branch

  git push origin feature/amazing-feature

• Open a Pull Request

Development Guidelines

• Follow React best practices and component patterns.
• Ensure responsive design for all components.
• Maintain accessibility standards.
• Write clear commit messages.
• Update documentation for new features.

📄 License

• This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Technologies & Services
  • Google Gemini API - For powerful natural language processing capabilities.
  • React Community - For excellent documentation and ecosystem.
  • Chart.js - For beautiful and accessible data visualizations.
  • Tailwind CSS - For efficient and consistent styling.
  • Netlify - For seamless deployment and hosting.
• Inspiration
  • Natural Language Processing research and applications.
  • User experience design principles for data visualization.
  • Open-source sentiment analysis tools and libraries.

💫 Support This Project If you find this sentiment analysis tool helpful, please consider giving it a ⭐️ on GitHub!

Built with ❤️ by Siyamthanda Dlakavu

Understanding emotions through technology, one analysis at a time.